About this Position
At FiscalNote, we build platforms that connect people to their government, and our Data Science team builds robust machine learning engines to make sure people can find the right information at the right time. As a Machine Learning (ML) Engineer, you’ll help scale and improve our data processing and analysis systems to productionize and implement highly scalable pipelines for our various data science services, including our natural language processing (NLP), search and information retrieval, recommendation engine, and knowledge graph technologies. You’ll work closely with our researchers, designers, and engineers to define performant solutions to complex open-ended problems, and play a critical role in delivering them to the thousands of organizations that depend on FiscalNote.
About the Team
The Research and Development (R&D) Department at FiscalNote is where the magic happens. The Department includes the Product, Data Science, Professional Services, and Technology Teams. These teams work together to develop and deliver solutions to FiscalNote’s clients. The FiscalNote Data Science team builds statistical, NLP, and ML-enabled services for intelligent data aggregation, manipulation, augmentation, and generation. Our team has a wealth of diverse life and career experiences that allow us to think outside of the box and ahead of the curve. We enjoy ending meetings by discussing our favorite theorems or nitpicking the latest news article on political models. You'll get the opportunity to work at an institution pushing the boundaries of open data transparency while collaborating with some of the industry’s brightest engineers and data scientists to devise, nurture, and implement cutting-edge solutions to continuously evolving engineering obstacles.
You are someone who loves to work on ambitious projects and pursues creative technological solutions to generalize patterns, extract connections, and surface relevant information across disparate datasets. You have experience in writing and extending machine learning code and related data services to serve multiple product use cases. You are passionate about code quality, continuous delivery, testing, and observability; frequently collaborating with team members to implement shared development patterns, thus enabling all to work more efficiently.
You have a working expertise in cloud infrastructure and are excited about productionizing research to push the bounds of people’s expectations. You are energized by ambiguity and enjoy finding optimizations in an ever-changing environment. You like working in an environment with multiple tech stacks. You apply an iterative development process, building a system that works end-to-end quickly before improving on it more deeply. You get a rush when you successfully orchestrate and automate several complex systems to work together.
You’re capable of working with ambiguity in a supportive but autonomous environment and are excited about solving complex problems by distilling them into simple solutions that work. You ground your work in software development frameworks while creating solutions that deliver the best results for user experience (including developer experience). Along the way, you’re comfortable proposing well-thought-out solutions and architectures to both technical and non-technical audiences, taking in stakeholder feedback while advocating for data science approaches that clearly demonstrate actionable, meaningful, and scalable solutions for business problems.
What to Expect in this Position:
- As an individual contributor on the data science team, you will collaborate with our data scientists, data engineers, and application engineers to build and extend our core back-end data systems to support a variety of use cases from analyzing search data, optimizing ranking algorithms, running controlled experiments, building scalable, high-performance models, and orchestrating data pipelines using various NLP, ML, and information retrieval techniques.
- You will participate in the full development cycle to design and deploy services to efficiently automate and productionize research solutions — integrating features that evaluate model quality, monitor drift and performance, provide interpretable assessments of recommendations or other model outputs.
- You will design processes to initiate validation and retraining and autonomously incorporate human-in-the-loop feedback mechanisms into production workflows.
- You will marshal various components of data systems from storage to access in order to connect large amounts of historical data from relational and graph databases, custom APIs, and server-side applications.
- You will partake in operational responsibility for data science services, performing analysis on infrastructure logs to troubleshoot issues and identify system failures and monitor data quality and event logs to estimate model performance.
- You will implement standards for optimization, testing, and tooling; recommending team best practices for deploying infrastructure (Databricks, Neo4j, Elasticsearch, Kubernetes) to support data scientists in the delivery of machine learning models.
- You will work across teams to ensure cohesion and collaboration across R&D functions (Devops, Engineering, QA, Data, etc.), explaining model applications for various user needs and advocating for data science solutions while keeping engineering quality and long-term design trade-offs in mind.
What Sets You Apart:
- 3-5 years of experience as a Machine Learning Engineer, Data Scientist, or Data Engineer
- Experience in the software development industry deploying ML-based services integrated via web applications, microservices, and data pipelines into production cloud environments
- Firm grasp of software engineering concepts and frameworks, such as OOP, various data structures (queues, trees, graphs, multi-dimensional arrays), computability and complexity, memory and cache management
- Knowledge of data pipelines and RESTful APIs (including Swagger/OpenAPI)
- Experience with Python-based applications and codebases, preferably familiarity with libraries for machine learning (e.g. sklearn) and NLP (e.g. Spacy)
- Strong understanding of machine learning (feature engineering, feature selection, optimization algorithms) and natural language processing (TFIDF, text classification, and word embeddings), demonstrated by the ability to dig deep into practical problems and choose the right ML method to solve them
- Experience with search engines, information retrieval systems, recommendation engines, personalization and ranking algorithms, bandits, reinforcement learning, or graph analytics is a plus
- Experience developing solutions with AWS tooling (S3, SSM, ECS, CodeDeploy)
- Experience with or willingness to learn Configuration Management and Cloud Provisioning Tools (at least one or more of the following - Docker, Kubernetes, Helm, Ansible, Terraform, Jenkins, Github Actions, CircleCI, CloudFormation)
- Familiarity with combining data across two or more different data stores and systems (PSQL, Oracle DB, Elasticsearch, Neo4j, Redis, Redshift, RMQ)
- Experience with batch-oriented distributed processing systems like Spark and Databricks is a plus
- Streaming platform (Kafka, Kinesis, Confluent) integration experience is a plus
- Knowledge of government or public policy datasets is a plus
FiscalNote is the premier information services company focused on global policy and market intelligence. By combining AI technology, expert analysis, and legislative, regulatory, and geopolitical data, FiscalNote is reinventing the way that organizations minimize risk and capitalize on opportunity.
Home to CQ, Roll Call, Oxford Analytica, and VoterVoice, FiscalNote empowers more than 5,000 clients worldwide to monitor, manage, and act on the issues that matter most to them. To learn more about FiscalNote and its family of brands, visit FiscalNote.com and follow @FiscalNote.
At FiscalNote, we Lead with Values
Know your Audience ? Find the Truth ? Drive Alignment ? Level Up ? Own the Job ? Bias for Action ? Support the Family
FiscalNote is continuing to hire new talent, with all interviewing and on-boarding done virtually due to COVID-19. New team members, along with our current staff, will temporarily work remotely (unless communicated otherwise).
If your background and experience align with the competencies above, we encourage you to apply so that we can review your experience and learn more about how you can add to FiscalNote’s growth and success.
FiscalNote offers competitive salaries, equity packages, and retirement accounts to ensure we’re all FN owners. We work hard, so our open vacation policy helps us ensure you’re getting the R&R you need. We offer comprehensive health, vision, and dental insurance options supplemented by a flexible spending account (FSA). We have a slew of other benefits which you can check out at careers.FiscalNote.com.
FiscalNote values diversity. We are committed to equal opportunities and creating an inclusive environment for all our employees. We welcome applicants regardless of ethnic origin, national origin, gender, race, religious beliefs, disability, sexual orientation or age. FiscalNote is an EEOC employer.
FiscalNote uses E-Verify to confirm the employment eligibility of all new employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.DHS.gov/E-Verify.